2011 Italian Stata Users Group meeting: Abstracts

Estimating the parameters of simultaneous-equations models with the sem command in Stata 12

David M. Drukker
This session serves as an introduction to Stata 12’s new sem command for estimating the parameters of simultaneous-equations models. Some of the considered models include unobserved factors. Estimation methods include maximum likelihood and generalized method of moments.


Funnelcompar: diagrammi a imbuto per la comparazione di performance sanitarie con aggiustamento per comparazioni multiple

Silvia Forni and Rosa Gini
Agenzia Regionale di Sanità della Toscana

Goodness-of-fit tests for categorical data: Comparing Stata, R, and SAS

Rino Bellocco and Sara Algeri
Università di Milano—Bicocca

ivtreatreg: A new Stata command for estimating binary treatment models with heterogeneous response to treatment under observable and unobservable selection

Giovanni Cerulli

sar: Automatic generation of statistical reports using Stata and Microsoft Word for Windows

Giovanni L. Lo Magno
Università degli studi di Palermo

Chained equations and more in multiple imputation in Stata 12

Yulia Marchenko
This session focuses on the new Stata 12 command, mi impute chained, to perform multivariate imputation using chained equations (ICE), also known as sequential regression imputation. ICE is a flexible imputation technique for imputing various types of data. The variable-by-variable specification of ICE allows the user to impute variables of different types by choosing the appropriate method for each variable from several univariate imputation methods. Variables can have an arbitrary missingdata pattern. By specifying a separate model for each variable, users are able to incorporate a number of important characteristics, such as ranges and restrictions within a subset, specific to each variable. Other new features in multiple imputation in Stata 12 will also be discussed.


Sequential logit models: Transition probabilities among nonalcoholic fatty liver disease (NAFLD) stages in a random sample population-based study from Southern Italy

Alberto Osella
IRCCS Saverio de Bellis
María Del Pilar Díaz
Universidad Nacional de Córdoba, Argentina

Evaluating individual player performance indexes in basketball with Stata

Giovanni Capelli
Università degli Studi di Cassino

Credit risk management and macroeconomic conditions

Ana-Maria Săndică and Alexie Ciprian Alupoaiei
Academy of Economic Studies—Bucharest

Wishes and grumbles

David Drukker
The “Wishes and grumbles” session offers participants the opportunity to highlight any problems or limitations of the software for the members of StataCorp attending the meeting, and to suggest possible improvements.





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